A synchronic lexical study of the Ede language continuum of West Africa: The effects of different similarity judgment criteria

In the context of a synchronic lexical study of the Ede varieties of West Africa, this paper investigates whether the use of different criteria sets to judge the similarity of lexical features in different language varieties yields matching conclusions regarding the relative relationships and clustering of the investigated varieties and thus leads to similar recommendations for further sociolinguistic research. Word lists elicited in 28 Ede varieties were analyzed with the inspection method. To explore the effects of different similarity judgment criteria, two different similarity judgment criteria sets were applied to the elicited data to identify similar lexical items. The quantification of these similarity decisions led to the computation of two similarity matrices which were subsequently analyzed by means of correlation analysis and multidimensional scaling. The findings of this analysis suggest compatible conclusions regarding the relative relationships and clustering of the investigated Ede varieties. However, the matching clustering results do not necessarily lead to the same recommendations for more in-depth sociolinguistic research, when interpreted in terms of an absolute lexical similarity threshold. The indicated ambiguities suggest the usefulness of focusing on the relative, rather than absolute in establishing recommendations for further sociolinguistic research.

GRASP with Hybrid Path Relinking for Bi-Objective Winner Determination in Combinatorial Transportation Auctions

The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.